Abstract
For comprehensive anatomical analysis of a mouse brain, accurate and efficient registration of the experimental brain samples to a reference atlas is necessary. Here, we introduce Bell Jar, a semiautomated solution that can align and annotate tissue sections with anatomical structures from a reference atlas as well as detect fluorescent signals with cellular resolution (e.g., cell bodies or nuclei). Bell Jar utilizes Mattes mutual information-directed B-spline transformations to achieve precise alignments, even with damaged sample tissues. While user input remains a requirement for fine-tuning section matches, the platform streamlines the process, aiding rapid analyses in high-throughput neuroanatomy studies. As a standalone desktop application with a user-friendly interface, Bell Jar's performance, which surpasses traditional manual and existing automated methods, can improve the reproducibility and throughput of histological analyses.
Keywords:
alignment; atlas registration; brain mapping; cell detection; cell quantification; neuroanatomy.